Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4966449 | Information Processing & Management | 2017 | 31 Pages |
Abstract
The experimental evaluation, performed on three state-of-the-art datasets, provided several outcomes: first, information extracted from the LOD cloud can significantly improve the performance of a graph-based RS. Next, experiments showed a clear correlation between the choice of the feature selection technique and the ability of the algorithm to maximize specific evaluation metrics, as accuracy or diversity of the recommendations. Moreover, our graph-based algorithm fed with LOD-based features was able to overcome several baselines, as collaborative filtering and matrix factorization.
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Authors
Cataldo Musto, Pierpaolo Basile, Pasquale Lops, Marco de Gemmis, Giovanni Semeraro,